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This dynamic chart analyzes the stock price of the FANG stocks from Jan 1st 2000 to Dec 31st 2016. This is a time series chart and the data source is FANG dataset from tidyquant package.

library(plotly)
library(tidyverse)
library(tidyquant)
library(ggplot2)

data("FANG") 
AMZN <- tq_get("AMZN", get = "stock.prices", from = "2000-01-01", to = "2016-12-31")

p <- AMZN %>%
    ggplot(aes(x = date, y = adjusted)) +
    geom_line(color = palette_light()[[1]]) + 
    scale_y_continuous() +
    labs(title = "AMZN Line Chart", 
         subtitle = "Continuous Scale", 
         y = "Closing Price", x = "") + 
    theme_tq()

ggplotly(p, tooltip = c("symbol"))
GOOG <- tq_get("GOOG", get = "stock.prices", from = "2000-01-01", to = "2016-12-31")

p <- GOOG %>%
    ggplot(aes(x = date, y = adjusted)) +
    geom_line(color = palette_light()[[2]]) + 
    scale_y_continuous() +
    labs(title = "GOOG Line Chart", 
         subtitle = "Continuous Scale", 
         y = "Closing Price", x = "") + 
    theme_tq()

ggplotly(p)
FB <- tq_get("FB", get = "stock.prices", from = "2000-01-01", to = "2016-12-31")

p <- FB %>%
    ggplot(aes(x = date, y = adjusted)) +
    geom_line(color = palette_light()[[3]]) + 
    scale_y_continuous() +
    labs(title = "FB Line Chart", 
         subtitle = "Continuous Scale", 
         y = "Closing Price", x = "") + 
    theme_tq()

ggplotly(p)
NFLX <- tq_get("NFLX", get = "stock.prices", from = "2000-01-01", to = "2016-12-31")

p <- NFLX %>%
    ggplot(aes(x = date, y = adjusted)) +
    geom_line(color = palette_light()[[4]]) + 
    scale_y_continuous() +
    labs(title = "NFLX Line Chart", 
         subtitle = "Continuous Scale", 
         y = "Closing Price", x = "") + 
    theme_tq()

ggplotly(p)